International Crude Oil Research Articles

Identifying dynamic risk spillovers between crude oil and downstream industries: China's futures market perspective.

Interactions between crude oil and its downstream products are crucial but complex. The main purpose of this study is to examine the risk spillover relationships between the crude oil futures market and the petrochemical downstream futures market in the context of the COVID-19 epidemic in China. By combining the dynamic conditional correlation-generalized autoregressive conditional heteroskedasticity (DCC-GARCH) model and the Diebold-Yilmaz spillover index based on time-varying parameter-vector autoregression (TVP-VAR-DY), we investigate the dynamic correlations between Shanghai crude oil futures (INE) and the downstream futures in China's petrochemical industry chain. At the same time, we also incorporate the representative global crude oil futures (BRENT and WTI) in our study as a comparative analysis. Our results show a significant positive correlation between three crude oil futures and China's downstream future products, with a more pronounced link observed between INE and the downstream futures market. Moreover, the correlation between crude oil futures and various downstream products exhibits heterogeneity; that is, direct derivatives of crude oil show higher sensitivity to price fluctuations compared to products with longer production chains. Furthermore, the spillover results indicate that the international crude oil futures, particularly BRENT, primarily function as spillover transmitters, while INE mainly serves as the recipient. In the post-pandemic period, the international crude oil market still exhibits a high spillover effect, and the spillover effect of INE to polyvinyl chloride, pure terephthalic acid, and bitumen futures increased, reflecting market recovery in China to some extent. These results provide potential insights for policymakers, financial institutions, industry participants, and investors, emphasizing the importance of enhanced risk management, diversified investment strategies, and attention to market dynamics.

The dependence structure and causality detection in crude oil markets

ABSTRACT It is essential to capture the dependence structure among the world’s dominant crude oil markets for understanding the world’s crude oil pricing mechanism. The dependence structure and interaction between Shanghai International Energy Exchange (INE) market and other major crude oil markets in the world are investigated to determine whether the world crude oil market is efficient. Using the vine copula model based on GARCH, we analyze the dependence structure and interactions among these markets. The highest dependence is found between West Texas Intermediate (WTI) and BRENT crude oil markets, displaying strong symmetric tail dependence. DUBAI market exhibits unidirectional Granger causality to WTI and INE markets. Empirical results suggest that the world crude oil markets are not efficient and are far from One Great Pool. DUBAI and Brent markets emerge as leaders in the current international crude oil pricing system, while INE markets do not significantly influence DUBAI and BRENT markets.

Spillover effects between fossil energy and green markets: Evidence from informational inefficiency

This paper builds an indicator of the market inefficiency degree by quantifying the extent of the market deviation from an efficient status. From a novel perspective of informational inefficiency, we further model the dynamic spillover effects between fossil energy and green markets by using a time-varying parameter vector autoregressive (TVP-VAR) model. Our findings indicate that the market inefficiency degree and its spillovers exhibit evident time-varying dynamics and are sensitive to extreme events. The international crude oil benchmarks serve as the most significant information transmitter and receiver in the spillover network of market inefficiency. Within green-related markets, carbon market demonstrates the strongest correlation with the fossil energy markets. Additional analyses involving consideration of economic policy uncertainty reassure the robustness of our findings.

Unveiling the Relationship Between Oil Price and Exchange Rate: New Insight from Time-varying Versus Fixed Coefficient Cointegration

This study provides a brief analysis of time-varying cointegration between the INR–USD bilateral exchange rate and Brent crude oil prices in the post–subprime crisis period. Prior studies established this relationship using the assumption that the long-run relation is intertemporally constant. However, there is much recent evidence demonstrating that this assumption may not be feasible. To address this issue and to go beyond the restrictive time-invariant environment, we employed the time-varying cointegration framework of Bierens and Martins (2010) , which was assessed through orthogonal Chebyshev time polynomials. The result shows that the Rupee was decoupled from oil price shocks in the first two samples. However, the oil price pass-through effect will become stronger in the third and fourth samples. The endogenous structural break test suggests the presence of serious parameter instabilities due to fluctuations in oil prices and the exchange rate over the period under study. This indicates the ability of international crude oil prices to influence domestic economic activities through the exchange rate. Policymakers should consider this factor while making monetary and foreign exchange policies. JEL Codes: E44, G14, G15

Effect of Selected Macroeconomic Variables on External Reserves Management in Nigeria (1981-2022)

This study examined the Effect of selected macroeconomic variables on External Reserves Management in Nigeria (1981-2022) with external reserves as a dependent variable and international crude oil price movement, exchange rate volatility, inflation, monetary policy rate, public expenditure, economic growth, external debt service payment, and trade Openness as independent variables. With dataset from the Central bank of Nigeria Statistical Bulletin and Autoregressive Distributive Lag (ARDL) model as the key estimation technique, the study found that crude price movement, economic growth, public expenditure growth, all had positive and significant impact on external reserves management. Exchange rate volatility, monetary policy rate and trade openness were found to have adverse and significant effects on external reserves. It is therefore recommended that effective and efficient fiscal and monetary policy measures be adopted to enhance the management of external reserves.

The Spillover Effects among Crude Oil Future Markets under High-Frequency Data Environment: Trivariate VAR-BEKK-GARCH Model Based on Wavelet Multiresolution Analysis

With the rapid development of financial globalization, the interconnection of international financial markets has deepened, and the relationship between domestic and international crude oil futures market price fluctuations has been increasingly strengthened. This paper utilizes 1-minute high-frequency price data of INE, WTI, and BRENT crude oil. By employing wavelet multiresolution analysis to address the ‘Calendar Effect’ present in intraday high-frequency data, and decomposing financial time series into different hierarchy of time scales. On this basis, the VAR-BEKK-GARCH model is established to study the spillover effect among the three crude oil future markets from the perspective of different trading cycles. The main conclusions of this paper are as follows: (1) The energy spectrum of wavelet multiresolution analysis shows that the price fluctuations of domestic and international crude oil futures are mainly reflected in the short-term trading cycles of 1-4 minutes; (2) The empirical results of the VAR-BEKK-GARCH model indicate that there are significant bidirectional mean and volatility spillover effects among INE, WTI, and BRENT crude oil in each trading cycle. Specifically, the mean spillover effect between INE and WTI markets shows that the short-term mean spillover effect of INE crude oil on WTI crude oil is larger, which is contrast to the medium- and long-term effect, and there is no significant pattern in the volatility spillover effect. The overall mean and volatility spillover effects of INE crude oil on BRENT crude oil are relatively larger. The overall mean and volatility spillover effects of WTI crude oil on BRENT crude oil are also relatively larger.

Leveraging machine learning to forecast carbon returns: Factors from energy markets

Carbon market is the most effective market tool for carbon emission reduction. China, the largest carbon emitter in the world, established the national carbon market in 2021, covering over 2000 key units in the power sector. Therefore, the forecasting of carbon price has profound implications for environmental and energy policies. In this paper, two traditional econometric model and three kinds of machine learning (ML) algorithms are used to predict carbon returns in the Chinese carbon trading market based on carefully selected predictors. Among all forecasting models, the Random Forest (RF) has the best forecasting performance, followed by some GARCH models using various factors. Compared with the traditional benchmark of ARMA model, the BP neural network (BP) and the GA improved BP method (GA-BP) are less competitive in predicting carbon returns in China because of their large forecasting errors. According to the optimal model, social attention to the carbon market, the international crude oil returns and the overall performance of the stock market are the most important predictors. The findings are robust to the change in the sample set. Overall, the ML approach shows an advantage in forecasting carbon returns, but the selection of predictors is also important.

Economic Variables as an Early Warning Sign for Monitoring Construction Cost Indices – “An Empirical Study on Egypt”

The construction industry plays a crucial role in any nation's economic growth and prosperity through the implementation of the SDGs. Researchers reveal that the 17 SDGs are directly dependent by 17% and indirectly reliant by 27% on the construction industry's activities. In addition, the construction projects, whatever their type or components, continue for several years, during which many price changes and sharp economic fluctuations occur, whether at the local or international level, reflected in overall economic performance and the construction industry's health, leading to the project's cost changes and a shortage in the allocated budgets. Due to the difficulties this industry faces in reaching these goals, including the Egypt Vision 2030, we chose to look into these effects by using the ENR methodology to develop an explanatory construction cost indices model in Egypt similar to models used in other countries while making appropriate changes for the Egyptian markets. To illustrate the relationship between these selected economic variables and construction costs in Egypt and to act as an early warning sign to quantify, track, and predict the construction cost movements and trends in Egypt's construction sectors through a reliable model. A mixed research methodology consisted of semi-structured interviews with 15 industry experts and an empirical study covering 1990 through 2020 for selected local and international economic variables. We concluded that national and international economic variables significantly impacted as explanatory and predictive variables in Egypt's construction industry's cost indices; these variables are as follows: gross domestic product (GDP), consumer price index (CPI), USD to EGP exchange rate ($), inflation rate, lending rate, money supply, and unemployment rate, as well as international crude oil prices, gold prices, and copper prices. Nevertheless, further investigation is required with more economic variables across various construction industry sectors over various time intervals and different time series statistical and econometric modeling techniques.

International oil shocks and the volatility forecasting of Chinese stock market based on machine learning combination models

This paper aims to forecast the volatility of Chinese stock market under the effects of international crude oil shocks. Eight individual models, including multiple linear regression (MLR), least absolute shrinkage and selection operator (LASSO), support vector regression (SVR), artificial neural network (ANN), recurrent neural network (RNN), long short-term memory (LSTM) network, gated recurrent unit (GRU) and bidirectional gated recurrent unit (BiGRU) are constructed. The realized volatilities of the CSI 300 index and ten primary sector indices are taken as explained variables, respectively. Four oil shock indicators and the autoregressive terms of the realized volatilities are taken as explanatory variables. The SHAP method is used to analyze their effects on the stock indices. Based on eight individual models, four kinds of combination models, i.e., a mean combination (Mean), a median combination (Median), a trimmed mean combination (Trimmed Mean), and two discount mean squared forecasting error combinations (DMSPE (1) and DMSPE (0.9)) are proposed. We compare forecasting performance between combination and individual ones. Empirical results show that the effects of international crude oil shocks on Chinese stock market are significant and have strong predictability. The effects on the energy, industry, optional consumption, and public sectors are greater than those on the CSI 300 and other sectors. Most of the combination models can effectively improve forecasting accuracy. In addition, by changing the benchmark model, the lengths of the rolling window, and the historical lengths of oil shock indicators, we find that most of the combination models are robust in volatility forecasting. This study is of guiding significance for individual and institutional investors to understand the operating mechanism of Chinese stock markets.

Price discovery of the Chinese crude oil options and futures markets

China's crude oil derivatives market has attracted extensive attention since its futures contracts were officially listed in 2018. This study examines the price discovery ability between Shanghai's crude oil options market and the corresponding futures market. Results show that futures lead options and the intraday distribution of options information share has a ‘w’ shape. Intraday seasonality of futures volume and the international crude oil market have significant impacts on the price discovery process. This study is the first empirical analysis of Shanghai crude oil options in terms of price discovery and presents novel insights into China's crude oil derivatives market.

On the Time-varying Correlations and Hedging Effectiveness: An Analysis of Crude Oil, Gold, and Stock Market

In this paper, we examine the time-varying conditional correlation between international crude oil and gold prices, along with their volatilities, and Indian stock prices, using the DCC-GARCH model. The results suggest that the relationships between stock/oil, stock/gold, stock/oil volatility, and stock/gold volatility are time-varying. We then use the conditional variance and covariance derived from the DCC-GARCH model to measure the optimal portfolio weight and hedge ratios for stock/oil and stock/gold portfolios. Our findings indicate that, to minimize risk without reducing expected returns, investors should hold 37% and 49% of oil and gold, respectively, in their portfolios, relative to stocks. However, there is wide variation in the hedge ratios over time, suggesting that portfolio managers will need to rebalance portfolios frequently. Finally, we analyze correlation coefficients under various deciles of stock market returns, showing that gold can be used as a hedge against stock market declines. Given India's significant improvement in financial indicators, the results of this study will be useful for portfolio managers, risk managers, policymakers, and researchers.

Risk spillover from international crude oil markets to China’s financial markets: Evidence from extreme events and U.S. monetary policy

We study the risk spillover from international crude oil markets to China’s financial markets by considering the shocks from extreme events and the moderating effect of U.S. monetary policy. Using the data of international oil markets and China’s financial markets from October 9, 2006, to March 8, 2022, we investigate the shocks of extreme events to risk spillover based on the GARCHSK-TVP-VAR-DY model with higher-order moments; we then empirically examine the moderating effect of the U.S. monetary policy (quantitative easing). The results reveal that (1) the international crude oil market has a significant net risk spillover effect on China’s financial markets; (2) the degree of spillover from the oil markets to the financial markets increases significantly under the shocks of extreme events; (3) the risk spillover effects of the oil markets on China’s various financial sub-markets are heterogeneous, with a more significant spillover to the commodity, foreign exchange, and monetary markets and a less significant spillover to the bond and stock market; and (4) U.S. quantitative easing policy alleviates the risk spillover effects of the oil market to Chinese financial markets, while U.S. monetary policies surpassing the conventional level may increase the risk spillover in the early stage of a severe crisis. Overall, this study has important implications for market participants and policymakers on spillover risk management.

International Crude Oil and Refined Products Trade, Year 2021

International Crude Oil and Refined Products Trade, Year 2021

International Crude Oil and Refined Products Trade, Year 2022

International Crude Oil and Refined Products Trade, Year 2022

Extreme risk contagion between international crude oil and China's energy-intensive sectors: New evidence from quantile Granger causality and spillover methods

We use quantile Granger causality and quantile spillover indices to analyze the connectedness of returns and volatility between crude oil and China's energy-intensive sectors (steel, electricity, coal, and petrochemical). The results show that both the strength and the direction of the connectedness are related to financial conditions (measured by quantiles), with the tail quantiles having much stronger connectedness than the middle level. Bidirectional Granger causality between crude oil and energy-intensive sectors occurs in the left (right) tail of returns as well as in the right tail of volatility. According to the quantile spillover indices, the spillover indices of crude oil's return and volatility are 2.79 % and 0.09 %, respectively, in the median condition, while they are as high as 71.09 % and 287.42 %, respectively, in the extreme condition. We emphasize that the volatility contagion from crude oil to energy-intensive sectors is significant only in the right tail quantiles. Among different sectors, the strongest connectedness between crude oil and the coal sector is observed at the extremes, followed by the petrochemical sector. The impact of China's energy-intensive sectors on the crude oil market deserves attention, as crude oil is a net receiver of information from China's energy-intensive sectors during certain periods.

Does the Russia-Ukraine conflict affect gasoline prices?

Geopolitical risk is an important factor driving the change in energy prices, especially the recent Russia-Ukraine conflict. The gasoline price is essential to national economic development and social stability. How does the Russia-Ukraine conflict affect gasoline prices in various countries? The paper constructs a regression discontinuity (RD) model to analyze the influence of the Russia-Ukraine conflict on gasoline prices to solve this problem. There are some important findings. (1) Gasoline prices in countries with greater than zero external dependence on crude oil are vulnerable to the Russia-Ukraine conflict. (2) The Russia-Ukraine conflict can increase gasoline prices by affecting international crude oil prices. (3) The Russia-Ukraine conflict can increase gasoline prices by affecting inflation rates. Some related policy suggestions are also proposed.

Risk Management Case Analysis of ICBC's "Crude Oil Treasure" Incident

Driven by the marketization of interest rates and technological innovation, commercial banks in China continue to innovate various financial services businesses and devote more attention to attracting customers to purchase various investment and wealth management products in order to expand sources of bank performance and gain more benefits. In 2018, paper crude oil-linked wealth management products emerged. Paper crude oil products are linked to the prices of international crude oil futures contracts. The products feature controllable risks and relatively high returns, which are very popular among large numbers of customers. However, despite the continuous expansion of China's financial derivatives trading volume, the categories of derivative products and regulation still have many limitations. The development of innovative paper crude oil-linked products is not perfect and has many potential risks, which are highly susceptible to market fluctuations. Taking China Bank's "Crude Oil Treasure" product as the research focus, this paper analyzes the massive loss incident that occurred in late April 2020 through case study analysis and qualitative analysis methods. It is divided into four parts. The introduction part explains the research background, significance, content, methods and innovations and inadequacies of this paper. The first part sorts out the background and process of the "Crude Oil Treasure" case at China Bank and elaborates on the operating principles of this product. The second part analyzes the "Crude Oil Treasure" case in detail. It first focuses on the problems in the product's trading liquidity, domestic and international time differences and product promotion. Then it focuses on the internal and external causes of the case, discussing external factors such as international crude oil market turmoil and futures trading characteristics, and internal factors such as product design, risk control and lack of experience. It also evaluates the hedging strategy, contract design and compliance of the "Crude Oil Treasure" product. The third part mainly analyzes the impacts of the "Crude Oil Treasure" rollover incident and China Bank's subsequent response measures. The fourth part puts forward certain countermeasures and suggestions from the perspectives of bank management, investors and regulatory agencies to prevent such incidents from recurring based on the case analysis.

The Impact of the Fed's Interest Rate Adjustment Cycle on the Price of WTI Crude Oil Futures

This article is based on monthly data from January 2016 to January 2022, including the US Federal Funds Rate and WTI crude oil futures price index. A TVP-VAR model is constructed to study the impact of the Federal Reserve's interest rate cycles on WTI crude oil futures prices. The research found a positive correlation between crude oil futures prices and the Federal Reserve's interest rate cycles. That means that when the Federal Reserve raises or lowers the US Federal Funds Rate, it leads to an increase or decrease in crude oil futures prices. Therefore, it is believed that in the current context of global quantitative easing and the sustained rise in international crude oil prices, China should formulate a new energy strategy that matches the high-quality development of the social economy and accelerate the transformation and upgrading of the crude oil industry.

Estimating the effect of international crude oil prices on RMB exchange rate with two-way fluctuation spillover.

International crude oil prices has become one of the important factors that affect exchange rate fluctuation. By combining TVP-VAR model and DY time-varying spillover index, this paper measures the two-way fluctuation spillover effect between international crude oil prices and RMB exchange rate from 2011 to 2022. The research results show that: (1) There are obvious time-varying characteristics among international crude oil prices, onshore RMB exchange rate and offshore RMB exchange rate, and they are strengthened when major events occur at home and abroad; (2) The spillover and absorption level among international crude oil prices, onshore RMB exchange rate and offshore RMB exchange rate is relatively limited; (3) After the "exchange rate reform on August 11", the market participation of RMB exchange rate has increased year by year, and the offshore RMB is mainly net spillover, while the onshore RMB is mainly reflected as a recipient; (4) The offshore RMB exchange rate has a driving effect on the onshore RMB exchange rate. Based on this, it is necessary to orderly promote the development and utilization of new energy, actively promote the market-oriented reform of RMB exchange rate, play the leading role of offshore market, and accelerate the construction of crude oil-RMB settlement system.

Factors Affecting Food Prices in Pakistan

The purpose of the study is to identify the factors affecting food prices in Pakistan. The findings reveal that there is a negative and significant impact of the real effective exchange rate on wheat prices in the long run. Similarly, the real interest rate affects wheat and rice prices indirectly, while it has a direct impact on tea prices. There is a positive and significant impact of international crude oil prices and international food prices on most food commodities. Moreover, the study explains that in the long run, the increase in local production significantly reduces the prices of food commodities. It is also found that the government policy of adjusting (increasing) wheat support prices also has a positive and significant impact on wheat prices.